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4,299,418 works, Canadian by any of four routes.

Every filter state is a URL; the URL is the query; the query is citable via /q/⟨hash⟩. The page, the API and the export parse the same parameters.

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The current cohort, streamed from the database: every work column, the machine labels, the provisional scores, and the per-row validation status. Exports are capped at 100,000 rows. Mints a permanent /q/ link for this exact query. The same filters always produce the same link, whoever asks.

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Muscle activation and electromyography studies
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Direct Codex and Gemma labels are unvalidated and sparse. Distilled predictions cover the full frame and are also unvalidated. Choose the evidence source explicitly; absence of a direct label is never a negative label.

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The four routes compose: require the funder route and exclude affiliation to get the funder-only stratum no affiliation-based frame ever sees.

3,432 results · 1 filter active ·
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20002025
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Machine labels · sparse coverage
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An unlabeled work is unknown, not a negative. Label coverage is reported on every query.
3,432 works in the cohort · of 4,299,418page 2 of 69

Labels cover 5 of 3,432 works in this cohort. The rest are unlabeled, which is not a negative label: the label table is sparse today and grows as labeling rounds land.

Distilled predictions cover 3,432 of 3,432 works in this cohort. Predictions are machine_predicted_unvalidated. The Gemma side is a direct model label for every work (title-only); the Codex side is a distilled, calibrated classifier. Candidate is the union; consensus is the intersection.

afffundunlabeled
Child—Adult Differences in Muscle Activation — A Review
Raffy Dotan, Cameron J. Mitchell, Rotem Cohen, Panagiota Klentrou, David A. Gabriel, Bareket Falk
2012· review· en· Pediatric Exercise Science· Engineering
machine prediction:candidate · noneconsensus · none
248
citations
affunlabeled
Testing the excitability of human motoneurons
Chris J. McNeil, Jane E. Butler, Janet L. Taylor, Simon C. Gandevia
2013· article· en· Frontiers in Human Neuroscience· Engineering
machine prediction:candidate · noneconsensus · none
219
citations
affno abstractunlabeled
Functional Electrical Stimulation and Spinal Cord Injury
Chester Ho, Ronald J. Triolo, Anastasia Elias, Kevin L. Kilgore, Anthony F. DiMarco, Kath M. Bogie +11 more
2014· review· en· Physical Medicine and Rehabilitation Clinics of North America· Engineering
machine prediction:candidate · noneconsensus · none
197
citations
afffundunlabeled
Gauging force by tapping tendons
Jack A. Martin, Scott C.E. Brandon, Emily M. Keuler, James Hermus, Alexander Ehlers, Daniel J. Segalman +2 more
2018· article· en· Nature Communications· Engineering
machine prediction:candidate · noneconsensus · none
193
citations
afffundno abstractunlabeled
Changing the texture of footwear can alter gait patterns
Matthew A. Nurse, M. Hulliger, James M. Wakeling, Benno M. Nigg, Darren J. Stefanyshyn
2005· article· en· Journal of Electromyography and Kinesiology· Engineering
machine prediction:candidate · noneconsensus · none
183
citations
affunlabeled
Skeletal muscle mechanics, energetics and plasticity
Richard L. Lieber, Thomas J. Roberts, Silvia S. Blemker, Sabrina S. M. Lee, Walter Herzog
2017· review· en· Journal of NeuroEngineering and Rehabilitation· Engineering
machine prediction:candidate · noneconsensus · none
171
citations
affunlabeled
Temporal Evolution of “Automatic Gain-Scaling”
J. Andrew Pruszynski, Isaac Kurtzer, Timothy Lillicrap, Stephen H. Scott
2009· article· en· Journal of Neurophysiology· Engineering
machine prediction:candidate · noneconsensus · none
169
citations
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How this was built: Screen · Findings · About